Programming languages evolve in steps. They began with weakly typed lan­ guages like FORTRAN and progressed to strongly typed languages like PAS­ CAL. This had the positive effect of moving the detection of many programming errors from run-time to compile-time. Unfortunately, it was soon recognized that it had the negative effect of limiting the generality of functions since they were now bound to a specific data type. This virtually eliminated the writing of reusable software components. The result was that programmers had to re-implement common algorithms and data structures over and over again. Newer languages, like C++, provide a way to decouple algorithms and data structures from the data types upon which they operate. C++ provides this capa­ bility via the template mechanism. Suddenly, it became possible to write generic algorithms and data structures that could be reused. In effect, this provides de­ bugged software components that can be combined to form programs much faster than by re-implementing the components each time they are needed. At the same time that programming languages were evolving, computer hard­ ware was becoming incredibly inexpensive compared to programmers'' salaries. This provided a strong incentive to reduce costs by increasing programmer pro­ ductivity. Software reuse was seen as one way to increase programmer productivity.

Programming languages evolve in steps. They began with weakly typed lan­ guages like FORTRAN and progressed to strongly typed languages like PAS­ CAL. This had the positive effect of moving the detection of many programming errors from run-time to compile-time. Unfortunately, it was soon recognized that it had the negative effect of limiting the generality of functions since they were now bound to a specific data type. This virtually eliminated the writing of reusable software components. The result was that programmers had to re-implement common algorithms and data structures over and over again. Newer languages, like C++, provide a way to decouple algorithms and data structures from the data types upon which they operate. C++ provides this capa­ bility via the template mechanism. Suddenly, it became possible to write generic algorithms and data structures that could be reused. In effect, this provides de­ bugged software components that can be combined to form programs much faster than by re-implementing the components each time they are needed. At the same time that programming languages were evolving, computer hard­ ware was becoming incredibly inexpensive compared to programmers'' salaries. This provided a strong incentive to reduce costs by increasing programmer pro­ ductivity. Software reuse was seen as one way to increase programmer productivity.

Programming languages evolve in steps. They began with weakly typed lan­ guages like FORTRAN and progressed to strongly typed languages like PAS­ CAL. This had the positive effect of moving the detection of many programming errors from run-time to compile-time. Unfortunately, it was soon recognized that it had the negative effect of limiting the generality of functions since they were now bound to a specific data type. This virtually eliminated the writing of reusable software components. The result was that programmers had to re-implement common algorithms and data structures over and over again. Newer languages, like C++, provide a way to decouple algorithms and data structures from the data types upon which they operate. C++ provides this capa­ bility via the template mechanism. Suddenly, it became possible to write generic algorithms and data structures that could be reused. In effect, this provides de­ bugged software components that can be combined to form programs much faster than by re-implementing the components each time they are needed. At the same time that programming languages were evolving, computer hard­ ware was becoming incredibly inexpensive compared to programmers'' salaries. This provided a strong incentive to reduce costs by increasing programmer pro­ ductivity. Software reuse was seen as one way to increase programmer productivity.